Optimizing Image Quality in Obese Patients Undergoing Coronary Computed Tomography (CT) Angiography

Overview

The purpose of this cardiovascular imaging research is to look at ways to improve the way we can look at the pictures of the heart. Patients undergo CT scans of the heart for a variety of reasons, including symptoms and/or tests suggestive of coronary artery disease (chest pain, shortness of breath, abnormal stress test, follow up exam of known/existing coronary disease, abnormal calcium score, etc.) This study involves finding ways to optimize quality of the scan in persons of size. This is because in patients with a BMI (body mass index) of greater than 40, it is usually difficult to "see" all the arteries around the heart satisfactorily. Body mass index is a number that we can get by putting your height and weight in a formula. The purpose of this study is to use a new computer software program to help us interpret your heart study.

Obesity is one of several known risk factors to develop CAD.The CT technology has been used in a multitude of important applications around the world, and many studies have established a high accuracy in detection of specific coronary stenoses (blockages in the arteries of the heart) compared to other non-invasive modalities and invasive coronary angiography, by heart catheterization. The accuracy of coronary CT angiography (CTA) in detecting coronary disease, as compared to cardiac catheterization has been demonstrated by previous studies performed at William Beaumont Hospital. Several factors contribute to the quality of the images seen on CTA, including heart rate and respiration. Overweight and obesity are also factors that influence image quality due to a low signal to noise ratio or a "noisy image". There are no studies examining the use of various techniques to improve image quality in this high-risk population of patients. Recent advances in multi-detector computed tomography angiography has made a noninvasive technique of diagnosis of coronary artery disease possible. Multi-detector computed tomography (MDCT) offers great promise as a risk stratification tool in patients with suspected CAD. It has been demonstrated in a multitude of accuracy studies to have a negative predictive value averaging over 95%. This leads to the hypothesis that a negative MDCT may preclude the need for invasive testing. The purpose of this study is to develop an optimal way to image obese patients without presenting an increased risk.